Elektrownie
Agnieszka Szymborska
29 listopad, 2017
Spis treści
Ładowanie bibliotek
library(dplyr)
library(ggplot2)
library('corrplot')
library(caret)
library(plotly)Wczytywanie danych z pliku
all_data <- read.csv(file="elektrownie.csv", header=TRUE, sep=",")Kod przetwarzający dane
Zmiana nazw kolumn
needed_data <- all_data %>% select(-icon, -(tempi:irri_pvgis_mod))
colnames(needed_data) <- c("measurementId", "place", "model", "brand", "latitude","longitude", "age", "year", "day", "hour", "date", "temperature", "radiation", "pressure", "windspeed", "humidity", "dewpoint", "bearing", "cloudcover", "energy")
needed_data$only_day <- as.numeric(format(as.POSIXct(factor(needed_data$date),format="%m/%d/%Y %H:%M"),"%d"))
needed_data$only_month <- as.numeric(format(as.POSIXct(factor(needed_data$date),format="%m/%d/%Y %H:%M"),"%m"))
needed_data$only_hour <- as.numeric(format(as.POSIXct(factor(needed_data$date),format="%m/%d/%Y %H:%M"),"%H"))
needed_data$place_string <- paste("place: ", as.character(needed_data$place))Uzupełnienie zerowych wartości
Wyodrębnienie modeli, marek oraz umiejscowienia czujników
W zbiorze występują dane dla 17 różnych lokalizacji. Lokalizację okreś
idbrands_with_models <- unique(needed_data[c("brand", "model")])
idmodels <- unique(needed_data$model)
idbrands <- unique(needed_data$brand)
idplaces <- unique(needed_data$place)
gps <- unique(needed_data[c("latitude", "longitude")])
gps_with_places_id <- unique(needed_data[c("latitude", "longitude", "place")])Podstawowe statystyki
| measurementId | place | model | brand | latitude | longitude | age | year | day | hour | date | temperature | radiation | pressure | windspeed | humidity | dewpoint | bearing | cloudcover | energy | only_day | only_month | only_hour | place_string | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min. : 1 | Min. :0.0000 | Min. :0.0000 | Min. :0.0000 | Min. :0.4150 | Min. :0.1540 | Min. :0.0000 | Min. :2012 | Min. :0.0000 | Min. :0.000 | 10/10/2012 10:00: 17 | Min. :0.0450 | Min. :0.0000 | Min. :0.0000 | Min. :0.00000 | Min. :0.1600 | Min. :0.1390 | Min. :0.0000 | Min. :0.000 | Min. :0.0000 | Min. : 1.00 | Min. : 1.000 | Min. : 1 | Length:235790 | |
| 1st Qu.: 99646 | 1st Qu.:0.1000 | 1st Qu.:0.1670 | 1st Qu.:0.0830 | 1st Qu.:0.4370 | 1st Qu.:0.6200 | 1st Qu.:0.0000 | 1st Qu.:2012 | 1st Qu.:0.2520 | 1st Qu.:0.222 | 10/10/2012 11:00: 17 | 1st Qu.:0.2120 | 1st Qu.:0.0000 | 1st Qu.:0.7480 | 1st Qu.:0.04200 | 1st Qu.:0.5400 | 1st Qu.:0.5350 | 1st Qu.:0.3000 | 1st Qu.:0.230 | 1st Qu.:0.0000 | 1st Qu.: 8.00 | 1st Qu.: 4.000 | 1st Qu.: 6 | Class :character | |
| Median :158594 | Median :0.2250 | Median :0.2080 | Median :0.1670 | Median :0.4370 | Median :0.6240 | Median :0.1250 | Median :2012 | Median :0.4770 | Median :0.500 | 10/10/2012 12:00: 17 | Median :0.3480 | Median :0.0350 | Median :0.7530 | Median :0.06600 | Median :0.7000 | Median :0.6190 | Median :0.4780 | Median :0.310 | Median :0.0490 | Median :16.00 | Median : 7.000 | Median :11 | Mode :character | |
| Mean :152703 | Mean :0.2147 | Mean :0.2426 | Mean :0.1519 | Mean :0.4495 | Mean :0.5711 | Mean :0.3145 | Mean :2012 | Mean :0.4812 | Mean :0.500 | 10/10/2012 13:00: 17 | Mean :0.3734 | Mean :0.1091 | Mean :0.6504 | Mean :0.07622 | Mean :0.6844 | Mean :0.6055 | Mean :0.4512 | Mean :0.359 | Mean :0.1688 | Mean :15.76 | Mean : 6.527 | Mean :11 | NA | |
| 3rd Qu.:217541 | 3rd Qu.:0.3250 | 3rd Qu.:0.2920 | 3rd Qu.:0.1670 | 3rd Qu.:0.4390 | 3rd Qu.:0.6300 | 3rd Qu.:0.7190 | 3rd Qu.:2013 | 3rd Qu.:0.7100 | 3rd Qu.:0.778 | 10/10/2012 14:00: 17 | 3rd Qu.:0.5300 | 3rd Qu.:0.2040 | 3rd Qu.:0.7550 | 3rd Qu.:0.10200 | 3rd Qu.:0.8400 | 3rd Qu.:0.6830 | 3rd Qu.:0.6600 | 3rd Qu.:0.510 | 3rd Qu.:0.3320 | 3rd Qu.:23.00 | 3rd Qu.:10.000 | 3rd Qu.:16 | NA | |
| Max. :276488 | Max. :0.4250 | Max. :0.7500 | Max. :0.4170 | Max. :0.5530 | Max. :0.6910 | Max. :1.0000 | Max. :2013 | Max. :1.0000 | Max. :1.000 | 10/10/2012 15:00: 17 | Max. :0.8180 | Max. :0.7100 | Max. :0.7690 | Max. :0.69600 | Max. :1.0000 | Max. :0.8650 | Max. :0.7690 | Max. :1.000 | Max. :1.0000 | Max. :31.00 | Max. :12.000 | Max. :20 | NA | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | (Other) :235688 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
